CN116579527A - Intelligent analysis management system for oil statistical data of enterprise - Google Patents
Intelligent analysis management system for oil statistical data of enterprise Download PDFInfo
- Publication number
- CN116579527A CN116579527A CN202310861259.4A CN202310861259A CN116579527A CN 116579527 A CN116579527 A CN 116579527A CN 202310861259 A CN202310861259 A CN 202310861259A CN 116579527 A CN116579527 A CN 116579527A
- Authority
- CN
- China
- Prior art keywords
- freight car
- automobile
- set period
- freight
- oil
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000004458 analytical method Methods 0.000 title claims abstract description 70
- 238000007726 management method Methods 0.000 claims abstract description 20
- 239000000446 fuel Substances 0.000 claims description 104
- 238000012423 maintenance Methods 0.000 claims description 88
- 238000011156 evaluation Methods 0.000 claims description 26
- 238000000034 method Methods 0.000 claims description 25
- 230000008569 process Effects 0.000 claims description 23
- 238000004364 calculation method Methods 0.000 claims description 21
- 230000036541 health Effects 0.000 claims description 20
- 238000012544 monitoring process Methods 0.000 claims description 16
- 238000010276 construction Methods 0.000 claims description 13
- 238000000605 extraction Methods 0.000 claims description 7
- 241001225883 Prosopis kuntzei Species 0.000 claims description 3
- 238000012937 correction Methods 0.000 claims description 3
- 238000012545 processing Methods 0.000 claims description 3
- 238000012216 screening Methods 0.000 claims description 2
- 238000013523 data management Methods 0.000 abstract description 3
- 238000007405 data analysis Methods 0.000 abstract 1
- 230000002159 abnormal effect Effects 0.000 description 7
- 238000011161 development Methods 0.000 description 4
- 230000008901 benefit Effects 0.000 description 2
- 230000007547 defect Effects 0.000 description 2
- 238000007792 addition Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 238000011835 investigation Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000001737 promoting effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/10—Office automation; Time management
- G06Q10/103—Workflow collaboration or project management
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/40—Business processes related to the transportation industry
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- Tourism & Hospitality (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Marketing (AREA)
- Physics & Mathematics (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Game Theory and Decision Science (AREA)
- Educational Administration (AREA)
- Development Economics (AREA)
- Data Mining & Analysis (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention belongs to the field of enterprise oil data analysis and management, and relates to an enterprise oil statistical data intelligent analysis and management system.
Description
Technical Field
The invention belongs to the field of analysis and management of enterprise oil data, and relates to an intelligent analysis and management system for enterprise oil statistical data.
Background
Along with the rapid development of economy and the steady improvement of living standard, the traffic demand is continuously expanded to meet the market demand and the demand of material circulation, and meanwhile, traffic business is gradually scaled and socialized, so that the rapid rise of traffic enterprises is promoted, the traffic enterprises comprise transportation means such as highways, railways, waterways and aviation, and the highway transportation is mostly implemented by adopting transportation means such as freight automobiles, and the normal running of the freight automobiles needs to consume a large amount of oil, so that the oil cost of the traffic enterprises is higher and the profit and the living ability of the traffic enterprises are directly influenced, and therefore, the management of the oil consumption condition of the freight automobiles under the name of the traffic enterprises is very necessary.
Compared with the previous mode of manually recording the oil data of the freight cars, the oil data management of the freight cars under the name of enterprises is greatly improved under the drive of economic rapid development, the oil data of the freight cars is obtained by managing the consumption amount of the oil card of the freight cars, the defect of low manual inspection efficiency is effectively avoided, but the oil data management system of the freight cars under the name of enterprises is reflected only by the proportion relation between the oil data of the freight cars and the driving mileage when the oil rationality of the freight cars is analyzed, and has the defects: 1. the influence of the health condition of the freight car on the car oil consumption is ignored, so that the rationality evaluation of the oil for the freight car by enterprises is incomplete, the problem of oil consumption cannot be accurately found, and corresponding measures cannot be taken to reduce the oil consumption.
2. The influence of the automobile bearing capacity on the automobile oil consumption during each transportation of the freight automobile is not considered, when the automobile bearing capacity exceeds the corresponding maximum allowable bearing capacity, the oil consumption is increased due to the increase of automobile resistance, the running speed of the automobile is influenced, the oil consumption of the automobile is further influenced, the analysis strength of the total oil consumption of the automobile is insufficient, the accuracy and the reliability of the oil rationality analysis of the freight automobile cannot be ensured, and the subsequent treatment of the freight automobile is influenced.
3. The method is characterized in that the method is lack of careful and accurate analysis on driving habits of drivers and influences of weather factors on vehicle oil consumption during each transportation of the freight car, so that the problem of oil consumption increase caused by negligence of speed and excessive braking force of the freight car in the transportation process is not considered, the influence of weather conditions on the running state of the freight car is not considered, the problem of automobile oil consumption is further influenced, and further the problem that the oil rationality analysis of the freight car is single and not persuasive is caused, and the management of enterprises on the freight car is not facilitated.
Disclosure of Invention
In view of this, in order to solve the problems set forth in the background art, an intelligent analysis management system for statistical data of oil for enterprises is proposed.
The aim of the invention can be achieved by the following technical scheme: the invention provides an intelligent analysis management system for oil statistical data of enterprises, which comprises the following components: and the automobile identity information input module is used for manually inputting the identity information of each freight automobile.
And the automobile related information extraction module is used for extracting the basic information, the transportation information and the history information of each freight automobile from the background of the enterprise according to the identity information of each freight automobile.
The automobile reference oil consumption analysis module is used for analyzing the reference oil consumption of each freight automobile in a fixed transportation path within a set period according to the basic information and the historical information of each freight automobile.
The automobile fuel consumption influence coefficient construction module is used for constructing fuel consumption influence coefficients of various freight automobiles in various transportation within a set period according to the basic information and transportation information of the various freight automobiles.
The automobile actual fuel consumption analysis module is used for analyzing the actual fuel consumption of each freight automobile in each transportation in the set period, and further obtaining the total fuel consumption of each freight automobile in the set period.
The automobile fuel filling amount obtaining module is used for obtaining the fuel filling amount of each freight automobile in the set period by extracting the consumption amount of the fuel filling card of each freight automobile in the set period from the gas station.
And the automobile oil rationality evaluation module is used for analyzing the oil rationality index of each freight automobile in the set period according to the total oil consumption and the oil filling amount of each freight automobile in the set period, and correspondingly processing the oil rationality index.
The cloud database is used for storing maintenance degree evaluation indexes corresponding to all parts of the automobile, maintenance grade evaluation indexes corresponding to all maintenance duration ranges of the automobile, storing total usable years, total running mileage and maximum allowed bearing weight of all types of automobiles specified by the automobile authorities, storing temperature influence factors, humidity influence factors, wind strength influence factors and rainfall and snowfall influence factors corresponding to the oil consumption of the automobile, and storing the unit price of oil cost in each time stage.
Preferably, the identity information includes a brand and a license plate number.
The basic information includes model number, specification, service life, total mileage, maintenance duration of each historical maintenance, mileage of each maintenance part and fixed transportation path.
The transportation information comprises the loading capacity, meteorological data and driving data of each transportation in a set period, wherein the meteorological data comprises the average temperature, the average humidity, the wind intensity and the rainfall and snowvolume of the same day, and the driving data comprises the braking force of each time and the vehicle speed of each monitoring time point.
The history information comprises the total mileage and total oil consumption of the running corresponding to the set period of each history period.
Preferably, the specific analysis process of the automobile reference oil consumption analysis module comprises the following steps: extracting the total mileage and total oil consumption of each historical period corresponding to the set period in the historical information of each freight car, and respectively recording asWherein i represents the number of each truck, < > and->P represents the number of each history age, < ->From the formulaAnd obtaining the fuel consumption of each freight car in unit mileage in a set period, wherein m represents the total historical age.
Extracting mileage of each truck fixed transportation path from basic information of each truckAnalyzing the reference fuel consumption of each truck in the fixed transportation path within the set period>The calculation formula is ∈>。
Preferably, the specific analysis process of the automobile fuel consumption influence coefficient construction module comprises the following steps: extracting model, specification and service life of each freight car from basic information of each freight carAnd total mileage travelled->Extracting the total service life and total mileage of each freight car specified by the automobile authorities from a cloud database according to the brand, model and specification of each freight car, and respectively marking the total service life and the total mileage as +.>Analyzing the use coefficient of each truck>The calculation formula is as follows:wherein->The weight duty factor of the usage coefficient corresponding to the set total mileage of the freight car and the service life is respectively expressed.
Extracting the maintenance duration of each historical maintenance of each freight car and each maintenance part from the basic information of each freight car, and correspondingly storing each part of the car according to the cloud databaseScreening out the maintenance degree evaluation index corresponding to each maintenance part of each historical maintenance of each freight car, further screening out the maximum value of the maintenance degree evaluation index of each maintenance part of each historical maintenance of each freight car as the maintenance degree judgment index of each historical maintenance of each freight car, and recording asWherein j represents the number of each history maintenance, < >>And then according to the maintenance duration of each historical maintenance of each freight car, extracting a maintenance grade evaluation index corresponding to the maintenance duration range of each historical maintenance of each freight car from the cloud database, and marking as +.>。
Analyzing the maintenance coefficient of each freight car, wherein the calculation formula is as followsWherein->And the correction factor of the set freight car maintenance coefficient is represented, and w represents the total number of historical maintenance times of the freight car.
According to the use coefficient and maintenance coefficient of each truck, the health condition index of each truck is analyzed, and the calculation formula is as follows:wherein->The weight ratio factors of the health indexes corresponding to the set truck use coefficient and maintenance coefficient are respectively represented, and e represents a natural constant.
The vehicle condition influence factors of the corresponding oil consumption of each freight vehicle are analyzed, and the calculation formula is as followsWherein->And indicating the set reasonable threshold value of the health condition index of the freight car.
Preferably, the specific analysis process of the automobile fuel consumption influence coefficient construction module further includes: extracting maximum allowable load weight corresponding to each freight car specified by the automobile authorities from a cloud database according to the brand, model and specification of each freight carExtracting the load of each transport in a set period from the transport information of each truck>Wherein r represents the number of each transportation of the freight car,/-for each transportation of the freight car>By the formula->And obtaining the bearing influence factors of the oil consumption corresponding to each transportation of each freight car in the set period.
According to the transportation information of each freight car, weather and driving influence factors of corresponding oil consumption of each freight car in each transportation in a set period are obtained and respectively recorded asThe fuel consumption influence coefficient of each freight car in each transportation in a set period is analyzed, and the calculation formula is as follows: />Wherein->Weight ratio factors of fuel consumption influence factors corresponding to load bearing, weather and driving influence factors respectively representing corresponding fuel consumption during transportation of set freight car>Representation->。
Preferably, the specific analysis process of the weather and driving influence factors of the corresponding oil consumption of each transportation of each freight car in the set period is as follows: the average temperature, average humidity, wind intensity and rainfall and snowfall of each transportation day in the set period are extracted from the transportation information of each freight car, the temperature grade, humidity grade, wind intensity grade and rainfall and snowfall grade of each transportation day in the set period of each freight car are obtained, the temperature grade, humidity grade, wind intensity grade and rainfall and snowfall grade of each transportation day of each freight car in the set period are extracted from a cloud database, and the temperature influence factors, humidity influence factors, wind intensity influence factors and rainfall and snowfall influence factors of the corresponding car oil consumption of each freight car in the set period are respectively recorded asThe weather influence factor of the oil consumption corresponding to each transportation of each freight car is calculated, and the formula is as follows: />。
Extracting the speed and braking force of each monitoring time point of each transport in a set period from the transport information of each truck, and respectively marking asG represents the number of each monitoring time point, +.>J represents the number of each brake, +.>By the formula->Obtaining each transport pair of each freight carDriving influencing factors of the fuel consumption, wherein ∈ ->Indicates the total number of monitoring time points, +.>Representing an emergency braking effort threshold specified by the vehicle manufacturer.
Preferably, the specific analysis process of the automobile actual fuel consumption analysis module is as follows: the actual fuel consumption of each transportation in each truck setting period is calculated, and the formula is as follows:the actual fuel consumption of each freight car in each transportation in the set period is accumulated to obtain the total fuel consumption of each freight car in the set period>。
Preferably, the specific analysis process of the automobile fuel filling amount acquisition module is as follows: acquiring the time stage of the set period, extracting the oil cost unit price d of the time stage of the set period from the cloud database, and obtaining the oil cost unit price d of the time stage of the set period according to the formulaObtaining the fuel filling quantity of each freight car in a set period, wherein +.>Representing the amount of the i-th freight car spent in the set period.
Preferably, the specific analysis process of the oil rationality evaluation module for the automobile is as follows: according to the total fuel consumption of each freight car in a set periodAnd fuel filling amount->Analyzing the rationality index of each truck in a set period>The calculation formula is as follows: />Wherein->And the set reasonable error value of the fuel consumption of the freight car is indicated.
Compared with the prior art, the invention has the following beneficial effects: (1) According to the invention, the reference oil consumption of the fixed transportation path of each freight car in the set period is calculated through the total mileage and the total oil consumption of each freight car in the set period corresponding to each historical period, so that a scientific basis is provided for the subsequent analysis of the total oil consumption of each freight car in the set period.
(2) According to the invention, the health state index of each freight car is analyzed from the two aspects of use and maintenance of each freight car, so that the health state of each freight car is intuitively and dataized, the influence of the health state of the car on the fuel consumption of the car is further considered, and the analysis of the total fuel consumption of each freight car in a set period is optimized.
(3) According to the invention, through the transportation information of each transportation in the set period of each freight car, the load bearing, weather and driving influence factors of the corresponding oil consumption of each transportation in the set period of each freight car are analyzed, the oil consumption influence coefficient of each transportation in the set period of each freight car is calculated by combining the health condition index, and the reliability and accuracy of the analysis of the total oil consumption of each subsequent freight car in the set period are ensured.
(4) According to the invention, the total fuel consumption of each freight car in the set period is analyzed by combining the reference fuel consumption of the fixed transportation path in the set period of each freight car and the fuel consumption influence coefficient of each transportation, so that the accuracy of analyzing the total fuel consumption of each freight car in the set period is improved, and powerful support is provided for the fuel consumption rationality analysis of each subsequent freight car in the set period.
(5) According to the invention, the total fuel consumption and the fuel filling amount in the set period of each freight car are processed, so that the fuel consumption rationality of each freight car in the set period is obtained through analysis, and accordingly, each freight car is processed, and the abnormal fuel consumption problem of each freight car is found in time, thereby reducing the fuel cost, improving the economic benefit of enterprises, and promoting the management health and orderly development of the enterprises better.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of a system according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the invention provides an intelligent analysis management system for oil statistics of enterprises, which comprises the following specific modules: the automobile fuel consumption system comprises an automobile identity information input module, an automobile related information extraction module, an automobile reference fuel consumption analysis module, an automobile fuel consumption influence coefficient construction module, an automobile actual fuel consumption analysis module, an automobile fuel filling amount acquisition module, an automobile fuel rationality evaluation module and a cloud database, wherein the connection relation among the modules is as follows: the automobile related information extraction module is connected with the automobile identity information input module, the automobile reference oil consumption analysis module is connected with the automobile related information extraction module, the automobile oil consumption influence coefficient construction module is connected with the automobile related information extraction module, the automobile reference oil consumption analysis module and the automobile oil consumption influence coefficient construction module are both connected with the automobile actual oil consumption analysis module, the automobile oil filling quantity acquisition module and the automobile actual oil consumption analysis module are both connected with the automobile oil rationality evaluation module, and the automobile oil consumption influence coefficient construction module and the automobile oil filling quantity acquisition module are both connected with the cloud database.
The automobile identity information input module is used for manually inputting the identity information of each freight automobile.
The automobile related information extraction module is used for extracting basic information, transportation information and historical information of each freight automobile from the background of an enterprise according to the identity information of each freight automobile.
Specifically, the identity information includes a brand and a license plate number.
The basic information includes model number, specification, service life, total mileage, maintenance duration of each historical maintenance, mileage of each maintenance part and fixed transportation path.
The transportation information comprises the loading capacity, meteorological data and driving data of each transportation in a set period, wherein the meteorological data comprises the average temperature, the average humidity, the wind intensity and the rainfall and snowvolume of the same day, and the driving data comprises the braking force of each time and the vehicle speed of each monitoring time point.
The history information comprises the total mileage and total oil consumption of the running corresponding to the set period of each history period.
The weather data is obtained by extracting the temperature, the humidity, the rainfall and the snow amount of each weather monitoring time point of the day and the wind intensity of the day from the weather platform through a wireless network by an enterprise background, carrying out average processing on the temperature and the humidity of each weather monitoring time point of the day to obtain the average temperature and the average humidity of the day, and accumulating the rainfall and the snow amount of each weather monitoring time point of the day to obtain the rainfall and the snow amount of the day.
The driving data are uploaded to the background of the enterprise through a driving data recorder on the freight car.
The automobile reference oil consumption analysis module is used for analyzing the reference oil consumption of each freight automobile in a fixed transportation path within a set period according to the basic information and the historical information of each freight automobile.
Specifically, the specific analysis process of the automobile reference oil consumption analysis module comprises the following steps: extracting the total mileage and total oil consumption of each historical period corresponding to the set period in the historical information of each freight car, and respectively recording asWherein i represents the number of each truck, < > and->P represents the number of each history age, < ->From the formulaAnd obtaining the fuel consumption of each freight car in unit mileage in a set period, wherein m represents the total historical age.
Extracting mileage of each truck fixed transportation path from basic information of each truckAnalyzing the reference fuel consumption of each truck in the fixed transportation path within the set period>The calculation formula is ∈>。
According to the embodiment of the invention, the reference oil consumption of the fixed transportation path of each freight car in the set period is calculated through the total mileage and the total oil consumption of each freight car in the set period corresponding to each historical period, so that a scientific basis is provided for the subsequent analysis of the total oil consumption of each freight car in the set period.
The automobile fuel consumption influence coefficient construction module is used for constructing fuel consumption influence coefficients of various freight automobiles in various transportation within a set period according to basic information and transportation information of the various freight automobiles.
Concrete embodimentsSpecifically, the specific analysis process of the automobile fuel consumption influence coefficient construction module comprises the following steps: extracting model, specification and service life of each freight car from basic information of each freight carAnd total mileage travelled->Extracting the total service life and total mileage of each freight car specified by the automobile authorities from a cloud database according to the brand, model and specification of each freight car, and respectively marking the total service life and the total mileage as +.>Analyzing the use coefficient of each truck>The calculation formula is as follows:wherein->The weight duty factor of the usage coefficient corresponding to the set total mileage of the freight car and the service life is respectively expressed.
The maintenance time length and the maintenance parts of each historical maintenance of each freight car are extracted from the basic information of each freight car, the maintenance degree evaluation indexes corresponding to the maintenance parts of each historical maintenance of each freight car are screened out according to the maintenance degree evaluation indexes corresponding to the parts of each freight car stored in the cloud database, and the maximum value of the maintenance degree evaluation indexes of the maintenance parts of each historical maintenance of each freight car is screened out and taken as the maintenance degree judgment index of each historical maintenance of each freight car and recorded asWherein j represents the number of each history maintenance, < >>And then according to the maintenance duration of each historical maintenance of each freight car, extracting a maintenance grade evaluation index corresponding to the maintenance duration range of each historical maintenance of each freight car from the cloud database, and marking as +.>。
Analyzing the maintenance coefficient of each freight car, wherein the calculation formula is as followsWherein->And the correction factor of the set freight car maintenance coefficient is represented, and w represents the total number of historical maintenance times of the freight car.
According to the use coefficient and maintenance coefficient of each truck, the health condition index of each truck is analyzed, and the calculation formula is as follows:wherein->The weight ratio factors of the health indexes corresponding to the set truck use coefficient and maintenance coefficient are respectively represented, and e represents a natural constant.
The vehicle condition influence factors of the corresponding oil consumption of each freight vehicle are analyzed, and the calculation formula is as followsWherein->And indicating the set reasonable threshold value of the health condition index of the freight car.
According to the embodiment of the invention, the health state of each freight car is intuitively and dataized by analyzing the health state index of each freight car from the two aspects of using and maintaining each freight car, so that the influence of the health state of each freight car on the fuel consumption of the car is considered, and the analysis of the total fuel consumption of each freight car in a set period is optimized.
Specifically, the specific analysis process of the automobile fuel consumption influence coefficient construction module further comprises the following steps: extracting maximum allowable load weight corresponding to each freight car specified by the automobile authorities from a cloud database according to the brand, model and specification of each freight carExtracting the load of each transport in a set period from the transport information of each truck>Wherein r represents the number of each transportation of the freight car,/-for each transportation of the freight car>By the formula->And obtaining the bearing influence factors of the oil consumption corresponding to each transportation of each freight car in the set period.
According to the transportation information of each freight car, weather and driving influence factors of corresponding oil consumption of each freight car in each transportation in a set period are obtained and respectively recorded asThe fuel consumption influence coefficient of each freight car in each transportation in a set period is analyzed, and the calculation formula is as follows: />WhereinWeight ratio factors of fuel consumption influence factors corresponding to load bearing, weather and driving influence factors respectively representing corresponding fuel consumption during transportation of set freight car>Representation->。
According to the embodiment of the invention, through the transportation information of each transportation in the set period of each freight car, the load bearing, weather and driving influence factors of the corresponding oil consumption of each transportation of each freight car in the set period are analyzed, the oil consumption influence coefficient of each transportation of each freight car in the set period is calculated by combining the health condition index, and the reliability and accuracy of the total oil consumption analysis of each subsequent freight car in the set period are ensured.
Specifically, the specific analysis process of the weather and driving influence factors of the corresponding oil consumption of each transportation of each freight car in the set period is as follows: the average temperature, average humidity, wind intensity and rainfall and snowfall of each transportation day in the set period are extracted from the transportation information of each freight car, the temperature grade, humidity grade, wind intensity grade and rainfall and snowfall grade of each transportation day in the set period of each freight car are obtained, the temperature grade, humidity grade, wind intensity grade and rainfall and snowfall grade of each transportation day of each freight car in the set period are extracted from a cloud database, and the temperature influence factors, humidity influence factors, wind intensity influence factors and rainfall and snowfall influence factors of the corresponding car oil consumption of each freight car in the set period are respectively recorded asThe weather influence factor of the oil consumption corresponding to each transportation of each freight car is calculated, and the formula is as follows:。
extracting the speed and braking force of each monitoring time point of each transport in a set period from the transport information of each truck, and respectively marking asG represents the number of each monitoring time point, +.>J represents the number of each brake, +.>By the formula->Obtaining driving influence factors of oil consumption corresponding to each transportation of each freight car, wherein +.>Indicates the total number of monitoring time points, +.>Representing an emergency braking effort threshold specified by the vehicle manufacturer.
The automobile actual fuel consumption analysis module is used for analyzing the actual fuel consumption of each freight automobile in each transportation in a set period and further obtaining the total fuel consumption of each freight automobile in the set period.
Specifically, the specific analysis process of the automobile actual fuel consumption analysis module is as follows: the actual fuel consumption of each transportation in each truck setting period is calculated, and the formula is as follows:the actual fuel consumption of each freight car in each transportation in the set period is accumulated to obtain the total fuel consumption of each freight car in the set period>。
According to the embodiment of the invention, the total fuel consumption of each freight car in the set period is analyzed by combining the reference fuel consumption of the fixed transportation path in the set period of each freight car and the fuel consumption influence coefficient of each transportation, so that the accuracy of analyzing the total fuel consumption of each freight car in the set period is improved, and powerful support is provided for the fuel consumption rationality analysis of each subsequent freight car in the set period.
The automobile fuel filling amount obtaining module is used for obtaining the fuel filling amount of each freight automobile in a set period by extracting the consumption amount of the fuel filling card of each freight automobile in the set period from a fuel filling station.
Specifically, the specific analysis process of the automobile fuel filling amount acquisition module is as follows:acquiring the time stage of the set period, extracting the oil cost unit price d of the time stage of the set period from the cloud database, and obtaining the oil cost unit price d of the time stage of the set period according to the formulaObtaining the fuel filling quantity of each freight car in a set period, wherein +.>Representing the amount of the i-th freight car spent in the set period.
The automobile oil rationality evaluation module is used for analyzing the oil rationality index of each freight automobile in a set period according to the total oil consumption and the oil filling amount of each freight automobile in the set period, and accordingly performing corresponding treatment.
Specifically, the specific analysis process of the oil rationality evaluation module for the automobile is as follows: according to the total fuel consumption of each freight car in a set periodAnd fuel filling amount->Analyzing the rationality index of each truck in a set period>The calculation formula is as follows: />Wherein->And the set reasonable error value of the fuel consumption of the freight car is indicated.
The specific process of the above-mentioned corresponding treatment is as follows: comparing the oil consumption rationality index of each freight car in the set period with the oil rationality index of the set freight car, if the oil consumption rationality index of a certain freight car in the set period is greater than or equal to the oil rationality index of the set freight car, recording the freight car as a normal oil consumption car, otherwise recording the freight car as an abnormal oil consumption car, obtaining abnormal oil consumption cars, sending the serial numbers of the abnormal oil consumption cars to enterprise staff in a short message mode, prompting the enterprise staff to conduct fault investigation on the abnormal oil consumption cars, and continuously monitoring the oil consumption data of the abnormal oil consumption cars in a future set period.
According to the embodiment of the invention, the total fuel consumption and the fuel filling amount in the set period of each freight car are processed, so that the fuel consumption rationality in the set period of each freight car is obtained through analysis, and accordingly, each freight car is processed, the problem of abnormal fuel consumption of each freight car is found in time, and further, the fuel cost is reduced, the economic benefit of enterprises is improved, and the management health and orderly development of the enterprises are better promoted.
The cloud database is used for storing maintenance degree evaluation indexes corresponding to all parts of the automobile, maintenance grade evaluation indexes corresponding to all maintenance duration ranges of the automobile, storing total usable years, total running mileage and maximum allowed bearing weight of all types of automobiles specified by the automobile authorities, storing temperature influence factors, humidity influence factors, wind strength influence factors and rainfall and snowfall influence factors corresponding to the oil consumption of the automobile, and storing the unit price of oil cost in each time stage.
The foregoing is merely illustrative and explanatory of the principles of this invention, as various modifications and additions may be made to the specific embodiments described, or similar arrangements may be substituted by those skilled in the art, without departing from the principles of this invention or beyond the scope of this invention as defined in the claims.
Claims (9)
1. An intelligent analysis management system for oil statistics of enterprises is characterized in that: the system comprises:
the automobile identity information input module is used for manually inputting the identity information of each freight automobile;
the automobile related information extraction module is used for extracting basic information, transportation information and history information of each freight automobile from the background of an enterprise according to the identity information of each freight automobile;
the automobile reference oil consumption analysis module is used for analyzing the reference oil consumption of each freight automobile in a fixed transportation path within a set period according to the basic information and the historical information of each freight automobile;
the automobile fuel consumption influence coefficient construction module is used for constructing fuel consumption influence coefficients of various freight automobiles in various transportation within a set period according to the basic information and transportation information of the various freight automobiles;
the automobile actual fuel consumption analysis module is used for analyzing the actual fuel consumption of each freight automobile in each transportation in a set period and further obtaining the total fuel consumption of each freight automobile in the set period;
the automobile fuel filling amount acquisition module is used for acquiring the fuel filling amount of each freight automobile in a set period by extracting the consumption amount of a fuel filling card of each freight automobile in the set period from a fuel station;
the automobile oil rationality evaluation module is used for analyzing the oil rationality index of each freight automobile in a set period according to the total oil consumption and the oil filling quantity of each freight automobile in the set period, and correspondingly processing the oil rationality index;
the cloud database is used for storing maintenance degree evaluation indexes corresponding to all parts of the automobile, maintenance grade evaluation indexes corresponding to all maintenance duration ranges of the automobile, storing total usable years, total running mileage and maximum allowed bearing weight of all types of automobiles specified by the automobile authorities, storing temperature influence factors, humidity influence factors, wind strength influence factors and rainfall and snowfall influence factors corresponding to the oil consumption of the automobile, and storing the unit price of oil cost in each time stage.
2. The intelligent analysis management system for oil statistics of enterprises according to claim 1, wherein: the identity information comprises a brand and a license plate number;
the basic information comprises model numbers, specifications, service life, total mileage travelled, maintenance duration of each historical maintenance, mileage of each maintenance part and fixed transportation path;
the transportation information comprises the loading capacity, meteorological data and driving data of each transportation in a set period, wherein the meteorological data comprises the average temperature, the average humidity, the wind intensity and the rainfall and snowquantity of the same day, and the driving data comprises the braking force of each time and the vehicle speed of each monitoring time point;
the history information comprises the total mileage and total oil consumption of the running corresponding to the set period of each history period.
3. The intelligent analysis management system for oil statistics of enterprises according to claim 2, wherein: the specific analysis process of the automobile reference oil consumption analysis module comprises the following steps: extracting the total mileage and total oil consumption of each historical period corresponding to the set period in the historical information of each freight car, and respectively recording asWherein i represents the number of each truck, < > and->P represents the number of each history age, < ->By the formula->Obtaining the oil consumption of unit mileage of each truck in a set period, wherein m represents the total historical age;
extracting mileage of each truck fixed transportation path from basic information of each truckAnalyzing the reference fuel consumption of each truck in the fixed transportation path within the set period>The calculation formula is ∈>。
4. An intelligent analysis and management system for oil statistics for enterprises according to claim 3, wherein: the specific analysis process of the automobile fuel consumption influence coefficient construction module comprises the following steps: extracting model, specification and service life of each freight car from basic information of each freight carAnd total mileage travelled->Extracting the total service life and total mileage of each freight car specified by the automobile authorities from a cloud database according to the brand, model and specification of each freight car, and respectively marking the total service life and the total mileage as +.>Analyzing the use coefficient of each truck>The calculation formula is as follows: />Wherein->Respectively representing the weight duty factor of the use coefficient corresponding to the set total mileage of the freight car which has been driven and the used period;
the maintenance duration and the maintenance parts of each historical maintenance of each freight car are extracted from the basic information of each freight car, and the maintenance corresponding to each maintenance part of each historical maintenance of each freight car is screened out according to the maintenance degree evaluation index corresponding to each part of the car stored in the cloud databaseThe maintenance degree evaluation index is further used for screening out the maximum value of the maintenance degree evaluation index of the maintenance parts of each historical maintenance of each freight car as the maintenance degree judgment index of each historical maintenance of each freight car, and is recorded asWherein j represents the number of each history maintenance, < >>And then according to the maintenance duration of each historical maintenance of each freight car, extracting a maintenance grade evaluation index corresponding to the maintenance duration range of each historical maintenance of each freight car from the cloud database, and marking as +.>；
Analyzing the maintenance coefficient of each freight car, wherein the calculation formula is as followsWhereinThe correction factor of the set freight car maintenance coefficient is represented, and w represents the total number of historical maintenance times of the freight car;
according to the use coefficient and maintenance coefficient of each truck, the health condition index of each truck is analyzed, and the calculation formula is as follows:wherein->The weight ratio factors of the health condition indexes corresponding to the set freight car use coefficients and the maintenance coefficients are respectively represented, and e represents a natural constant;
the vehicle condition influence factors of the corresponding oil consumption of each freight vehicle are analyzed, and the calculation formula is as followsWherein->And indicating the set reasonable threshold value of the health condition index of the freight car.
5. The intelligent analysis and management system for oil statistics of enterprises according to claim 4, wherein: the specific analysis process of the automobile fuel consumption influence coefficient construction module further comprises the following steps: extracting maximum allowable load weight corresponding to each freight car specified by the automobile authorities from a cloud database according to the brand, model and specification of each freight carExtracting the load of each transport in a set period from the transport information of each truck>Wherein r represents the number of each transportation of the freight car,/-for each transportation of the freight car>By the formula->Obtaining a bearing influence factor of oil consumption corresponding to each transportation of each freight car in a set period;
according to the transportation information of each freight car, weather and driving influence factors of corresponding oil consumption of each freight car in each transportation in a set period are obtained and respectively recorded asThe fuel consumption influence coefficient of each freight car in each transportation in a set period is analyzed, and the calculation formula is as follows: />Wherein->Weight ratio factors of fuel consumption influence factors corresponding to load bearing, weather and driving influence factors respectively representing corresponding fuel consumption during transportation of set freight car>Representation->。
6. The intelligent analysis management system for oil statistics of enterprises according to claim 5, wherein: the specific analysis process of the weather and driving influence factors of the oil consumption corresponding to each transportation of each freight car in the set period is as follows: the average temperature, average humidity, wind intensity and rainfall and snowfall of each transportation day in the set period are extracted from the transportation information of each freight car, the temperature grade, humidity grade, wind intensity grade and rainfall and snowfall grade of each transportation day in the set period of each freight car are obtained, the temperature grade, humidity grade, wind intensity grade and rainfall and snowfall grade of each transportation day of each freight car in the set period are extracted from a cloud database, and the temperature influence factors, humidity influence factors, wind intensity influence factors and rainfall and snowfall influence factors of the corresponding car oil consumption of each freight car in the set period are respectively recorded asThe weather influence factor of the oil consumption corresponding to each transportation of each freight car is calculated, and the formula is as follows: />；
Extracting the speed and braking force of each monitoring time point of each transport in a set period from the transport information of each truck, and respectively marking asG representsNumber of each monitoring time point, +.>J represents the number of each brake, +.>By the formula->Obtaining driving influence factors of oil consumption corresponding to each transportation of each freight car, wherein +.>Indicates the total number of monitoring time points, +.>Representing an emergency braking effort threshold specified by the vehicle manufacturer.
7. The intelligent analysis management system for oil statistics of enterprises according to claim 5, wherein: the specific analysis process of the automobile actual fuel consumption analysis module is as follows: the actual fuel consumption of each transportation in each truck setting period is calculated, and the formula is as follows:the actual fuel consumption of each freight car in each transportation in the set period is accumulated to obtain the total fuel consumption of each freight car in the set period>。
8. The intelligent analysis management system for oil statistics of enterprises according to claim 7, wherein: the specific analysis process of the automobile fuel filling amount acquisition module is as follows: acquiring the time stage of the set period, extracting the oil cost unit price d of the time stage of the set period from the cloud database, and obtaining the oil cost unit price d of the time stage of the set period according to the formulaObtaining the fuel filling quantity of each freight car in a set period, wherein +.>Representing the amount of the i-th freight car spent in the set period.
9. The intelligent analysis management system for oil statistics of enterprises according to claim 8, wherein: the specific analysis process of the oil rationality evaluation module for the automobile comprises the following steps: according to the total fuel consumption of each freight car in a set periodAnd fuel filling amount->Analyzing the rationality index of each truck in a set period>The calculation formula is as follows:wherein->And the set reasonable error value of the fuel consumption of the freight car is indicated.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310861259.4A CN116579527A (en) | 2023-07-14 | 2023-07-14 | Intelligent analysis management system for oil statistical data of enterprise |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310861259.4A CN116579527A (en) | 2023-07-14 | 2023-07-14 | Intelligent analysis management system for oil statistical data of enterprise |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116579527A true CN116579527A (en) | 2023-08-11 |
Family
ID=87541708
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310861259.4A Pending CN116579527A (en) | 2023-07-14 | 2023-07-14 | Intelligent analysis management system for oil statistical data of enterprise |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116579527A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117114209A (en) * | 2023-10-23 | 2023-11-24 | 湖北君邦环境技术有限责任公司 | Method, device and equipment for predicting carbon emission of automobile in full life cycle |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20060026314A (en) * | 2004-09-20 | 2006-03-23 | 김춘동 | Car value liquidation system and management method thereof |
| JP2009250930A (en) * | 2008-04-10 | 2009-10-29 | Nissan Motor Co Ltd | Fuel consumption information processing system and fuel consumption information displaying technique |
| CN201494247U (en) * | 2009-09-07 | 2010-06-02 | 威海万丰奥威汽轮有限公司 | Vehicle wheel with material drawing slot |
| CN201754094U (en) * | 2010-03-15 | 2011-03-02 | 北京联诚罗杰科技发展有限公司 | Automobile fuel consumption monitor |
| KR101699884B1 (en) * | 2016-05-18 | 2017-01-26 | 유비씨엔(주) | Mmanagement system and method of customized vehicle maintenance using OBD and GPS information |
| CN107239844A (en) * | 2016-03-28 | 2017-10-10 | 武汉长江通信智联技术有限公司 | A kind of petroleum transportation vehicle oil consumption Forecasting Methodology based on Hadoop |
| CN111523701A (en) * | 2020-03-27 | 2020-08-11 | 广州亚美信息科技有限公司 | Method and device for evaluating vehicle running condition, computer equipment and storage medium |
| WO2022062569A1 (en) * | 2020-09-24 | 2022-03-31 | 华为技术有限公司 | Vehicle energy consumption scoring method and device |
| WO2022236751A1 (en) * | 2021-05-12 | 2022-11-17 | 华为技术有限公司 | Battery state of charge estimation method and device |
-
2023
- 2023-07-14 CN CN202310861259.4A patent/CN116579527A/en active Pending
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20060026314A (en) * | 2004-09-20 | 2006-03-23 | 김춘동 | Car value liquidation system and management method thereof |
| JP2009250930A (en) * | 2008-04-10 | 2009-10-29 | Nissan Motor Co Ltd | Fuel consumption information processing system and fuel consumption information displaying technique |
| CN201494247U (en) * | 2009-09-07 | 2010-06-02 | 威海万丰奥威汽轮有限公司 | Vehicle wheel with material drawing slot |
| CN201754094U (en) * | 2010-03-15 | 2011-03-02 | 北京联诚罗杰科技发展有限公司 | Automobile fuel consumption monitor |
| CN107239844A (en) * | 2016-03-28 | 2017-10-10 | 武汉长江通信智联技术有限公司 | A kind of petroleum transportation vehicle oil consumption Forecasting Methodology based on Hadoop |
| KR101699884B1 (en) * | 2016-05-18 | 2017-01-26 | 유비씨엔(주) | Mmanagement system and method of customized vehicle maintenance using OBD and GPS information |
| CN111523701A (en) * | 2020-03-27 | 2020-08-11 | 广州亚美信息科技有限公司 | Method and device for evaluating vehicle running condition, computer equipment and storage medium |
| WO2022062569A1 (en) * | 2020-09-24 | 2022-03-31 | 华为技术有限公司 | Vehicle energy consumption scoring method and device |
| WO2022236751A1 (en) * | 2021-05-12 | 2022-11-17 | 华为技术有限公司 | Battery state of charge estimation method and device |
Non-Patent Citations (3)
| Title |
|---|
| ZHONGMIN LIU ETAL.: "Experimental study on the oil pump driving energy consumption and lubrication safety in a PFI engine under NEDC and WLTC", JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY * |
| 刘建民等: "《物流运输车辆管理》", 四川科学技术出版社, pages: 153 - 155 * |
| 单飞;王国伟;: "基于行驶工况的单车燃油消耗微观模型", 公路与汽运, no. 06 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117114209A (en) * | 2023-10-23 | 2023-11-24 | 湖北君邦环境技术有限责任公司 | Method, device and equipment for predicting carbon emission of automobile in full life cycle |
| CN117114209B (en) * | 2023-10-23 | 2024-02-06 | 湖北君邦环境技术有限责任公司 | Method, device and equipment for predicting carbon emission of automobile in full life cycle |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Husnjak et al. | Telematics system in usage based motor insurance | |
| US20160078695A1 (en) | Method and system for managing a fleet of remote assets and/or ascertaining a repair for an asset | |
| CN102610088B (en) | Method for forecasting travel time between bus stops | |
| US20020059075A1 (en) | Method and system for managing a land-based vehicle | |
| CN116579527A (en) | Intelligent analysis management system for oil statistical data of enterprise | |
| CN109815912B (en) | Highway safety inspection system based on artificial intelligence | |
| CN111680936A (en) | Traffic carbon emission monitoring method and device and terminal equipment | |
| CN107918826B (en) | Driver evaluation and scheduling method for driving environment perception | |
| CN109035768B (en) | Method for identifying taxi detour behavior | |
| CN115375234A (en) | GNSS-based transportation vehicle operation track planning method | |
| CN116050853A (en) | Wind control method and system for net cargo freight bill | |
| CN106570182B (en) | Method and system for identifying getting-off station of bus | |
| CN112767686B (en) | Road network automobile emission estimation method based on multi-source data fusion | |
| CN117114175B (en) | Prediction method for realizing foreign trade goods delivery scheduling based on Beidou positioning technology | |
| CN106021547B (en) | Customer vehicle maintenance loss identification and analysis method and system based on Internet of vehicles | |
| CN117035422A (en) | Method for predicting freight train line transportation risk | |
| CN114524004B (en) | Locomotive operation statistical method, device, equipment and storage medium | |
| CN114414016B (en) | Target vehicle detection method and device, storage medium and electronic equipment | |
| CN110686700B (en) | Railway wagon running mileage statistical method and system | |
| CN115829270A (en) | Intelligent operation and maintenance system of railway wagon | |
| CN115424448A (en) | Traffic carbon emission evaluation method and system based on traffic travel data | |
| CN115271565A (en) | DEA-based method, device and equipment for evaluating highway pavement maintenance measures | |
| CN115083155A (en) | Method for measuring and calculating number of ETC lanes due to highway toll station | |
| Ślęzak et al. | Comparative analysis of reliability and maintenance costs of heavy goods vehicles of selected brands used under long-term rental | |
| CN117636653B (en) | Expressway traffic carbon emission measuring and calculating method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20230811 |